Planning For High Performance Web Application

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Shootout at the AWS Corral

This talk was given during DockerCon EU 2018. It ain't just a whim - to be able to continue innovating, we’ve moved our good old static production to containers. We needed to be elastic, fast, reliable and production ready at any time - that's why we chose Docker. But like in most enterprises, lots of our apps run on the JVM and most JVMs’ ergonomics assume they “own” the server they are running on. So how do you containerize JVM apps? Should you really increase JVM heap if you have spare memory? What about OS caches? What are the differences between JDK 8, 9 and 10 when it comes to container awareness? Outages because of out of memory errors? Slowness because of long garbage collection and poor environment visibility? Long story short, in this session, we’ll look at the gotchas of running JVM apps in containers and teach you how to avoid costly mistakes. Top 3 things attendees will learn: 1. Key differences between various JVM versions relevant for containerized Java apps. 2. Best practices for running JVM in containers. 3. Avoiding common pitfalls when running containerized JVM applications.

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High Availability PostgreSQL with Zalando Patroni

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Postgres is a popular relational database and is the backend of a number of high traffic applications. Join AWS and PalominoDB, the company that helped Obama for America campaign optimize the database infrastructure on AWS, to learn about how you can run high throughput, I/O intensive Postgres clusters on the Amazon EBS storage platform. We will go over best practices including performance, durability and optimization related to deploying Postgres on AWS. You hear about the best practices learned and applied for the Obama for America campaign. In this webinar, you will learn about: - Amazon Elastic Block Store (EBS) - Why Provisioned IOPS volumes fit the needs of high I/O intensive applications - Best practices for deploying Postgres on AWS - How to leverage Provisioned IOPS volumes for Postgres

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Docker offers a new, lightweight approach to application portability. Applications are shipped using a common container format, and managed with a high-level API. Their processes run within isolated namespaces which abstract the operating environment, independently of the distribution, versions, network setup, and other details of this environment. This "containerization" has often been nicknamed "the new virtualization". But containers are more than lightweight virtual machines. Beyond their smaller footprint, shorter boot times, and higher consolidation factors, they also bring a lot of new features and use cases which were not possible with classical virtual machines. We will focus on one of those features: separation of operational concerns. Specifically, we will demonstrate how some fundamental tasks like logging, remote access, backups, and troubleshooting can be entirely decoupled from the deployment of applications and services. This decoupling results in independent, smaller, simpler moving parts; just like microservice architectures break down large monolithic apps in more manageable components.

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Apache Performance Tuning: Scaling Up

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Netflix tunes Amazon EC2 instances for maximum performance. In this session, you learn how Netflix configures the fastest possible EC2 instances, while reducing latency outliers. This session explores the various Xen modes (e.g., HVM, PV, etc.) and how they are optimized for different workloads. Hear how Netflix chooses Linux kernel versions based on desired performance characteristics and receive a firsthand look at how they set kernel tunables, including hugepages. You also hear about Netflix's use of SR-IOV to enable enhanced networking and their approach to observability, which can exonerate EC2 issues and direct attention back to application performance.

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HighLoad++ 2017 Зал «Кейптаун», 8 ноября, 17:00 Тезисы: http://www.highload.ru/2017/abstracts/3096.html PostgreSQL is the world’s most advanced open source database. Indeed! With around 270 configuration parameters in postgresql.conf, plus all the knobs in pg_hba.conf, it is definitely ADVANCED! How many parameters do you tune? 1? 8? 32? Anyone ever tuned more than 64? No tuning means below par performance. But how to start? Which parameters to tune? What are the appropriate values? Is there a tool --not just an editor like vim or emacs-- to help users manage the 700-line postgresql.conf file? Join this talk to understand the performance advantages of appropriately tuning your postgresql.conf file, showcase a new free tool to make PostgreSQL configuration possible for HUMANS, and learn the best practices for tuning several relevant postgresql.conf parameters.

PostgreSQL Configuration for Humans / Alvaro Hernandez (OnGres)

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[NYC Meetup] Docker at Nuxeo

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Nagios Conference 2014 - Jeff Mendoza - Monitoring Microsoft Azure with Nagios

Nagios

This talk was given during Lucene Revolution 2017 and has two goals: first, to discuss the tradeoffs for running Solr on Docker. For example, you get dynamic allocation of operating system caches, but you also get some CPU overhead. We'll keep in mind that Solr nodes tend to be different than your average container: Solr is usually long running, takes quite some RSS and a lot of virtual memory. This will imply, for example, that it makes more sense to use Docker on big physical boxes than on configurable-size VMs (like Amazon EC2). The second goal is to discuss issues with deploying Solr on Docker and how to work around them. For example, many older (and some of the newer) combinations of Docker, Linux Kernel and JVM have memory leaks. We'll go over Docker operations best practices, such as using container limits to cap memory usage and prevent the host OOM killer from terminating a memory-consuming process - usually a Solr node. Or running Docker in Swarm mode over multiple smaller boxes to limit the spread of a single issue.

Solr on Docker - the Good, the Bad and the Ugly

Sematext Group, Inc.

Запускаем сервер (БД, Web-сервер или что-то свое собственное) и не получаем желаемый RPS. Запускаем top и видим, что 100% выедается CPU. Что дальше, на что расходуется процессорное время? Можно ли подкрутить какие-то ручки, чтобы улучшить производительность? А если параметр CPU не высокий, то куда смотреть дальше? Мы рассмотрим несколько сценариев проблем производительности, рассмотрим доступные инструменты анализа производительности и разберемся в методологии оптимизации производительности Linux, ответим на вопрос за какие ручки и как крутить.

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Monitoring MongoDB’s Engines in the Wild

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Learn the specifics of Amazon RDS for PostgreSQL’s capabilities and extensions that make it powerful. This session begins with a brief overview of the RDS PostgreSQL service, how it provides High Availability & Durability and will then deep dive into the new features that we have released since re:Invent 2014, including major version upgrade and newly added PostgreSQL extensions to RDS PostgreSQL. During the session, we will also discuss lessons learned running a large fleet of PostgreSQL instances, including specific recommendations. In addition we will present benchmarking results looking at differences between the 9.3, 9.4 and 9.5 releases.

(DAT402) Amazon RDS PostgreSQL:Lessons Learned & New Features

Amazon Web Services

Apache Cassandra makes it possible to execute millions of operations per second in scalable fashion. Harnessing the power of C* leaves many developers pondering about the following: - Is my data model appropriate and not going to end up as wide partition(s) causing heap pressure and other issues? - How do I tune my connection pool configuration? What are the optimal settings for my environment ? - What is my C* cluster capacity in terms of number of IOPs for a given 95th and 99th latency? - How do I perf-test my data access layer? In this talk, Vinay Chella, Cloud Data Architect @ Netflix, will share open source tools, techniques and platform(NDBench) that Netflix uses to perf-test their C* fleet with simulations millions of operations per second. About the Speaker Vinay Chella Cloud Data Architect, NETFLIX Inc About Vinay Chella, Cloud Data Architect at Netflix having deeper understanding of Cassandra and other RDBMS. As an Engineer and Architect, working extensively on data modeling, performance tuning and guiding best practices of various persistence stores. Helping various teams @ Netflix building next generation data access layers.

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DataStax

Josh Berkus Most users know that PostgreSQL has a 23-year development history. But did you know that Postgres code is used for over a dozen other database systems? Thanks to our liberal licensing, many companies and open source projects over the years have taken the Postgres or PostgreSQL code, changed it, added things to it, and/or merged it into something else. Illustra, Truviso, Aster, Greenplum, and others have seen the value of Postgres not just as a database but as some darned good code they could use. We'll explore the lineage of these forks, and go into the details of some of the more interesting ones.

Elephant Roads: a tour of Postgres forks

Command Prompt., Inc

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Shootout at the AWS Corral

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Containerization is more than the new Virtualization: enabling separation of ...

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Monitoring MongoDB’s Engines in the Wild

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The Open source market is getting overcrowded with different Network monitoring solutions, and not without reason, monitoring your infrastructure become more important each day, you have to know what's going on for your boss, your customers and for yourself. Nagios started the evolution, but today OpenNMS, Zabix, Zenoss, Groundworks, Hyperic and different others are showing up in the market. Do you want lightweight, or feature full, how far do you want to go with your monitoring, just on os level, or do you want to dig into your applications, do you want to know how many query per seconds your MySQL database is serving, or do you want to know about the internal state of your JBoss, or be triggered if the OOM killer will start working soon. This presentation will guide the audience trough the different alternatives, based on our experiences in the field. We will be looking both at alerting and trending and how easy or difficult it is to deploy such an environment.

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En esta sesión voy a contar las decisiones técnicas que tomamos al desarrollar QuestDB, una base de datos Open Source para series temporales compatible con Postgres, y cómo conseguimos escribir más de cuatro millones de filas por segundo sin bloquear o enlentecer las consultas. Hablaré de cosas como (zero) Garbage Collection, vectorización de instrucciones usando SIMD, reescribir en lugar de reutilizar para arañar microsegundos, aprovecharse de los avances en procesadores, discos duros y sistemas operativos, como por ejemplo el soporte de io_uring, o del balance entre experiencia de usuario y rendimiento cuando se plantean nuevas funcionalidades.

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Explaining why you should and how you can test your web application using JMeter test plans to determine the scalability. By knowing how good or bad your application performs you can then make the decision to optimize it. But where to start optimizing? => You need to profile your application in order to see the components which have the most impact in your application regarding number of method calls, memory consumption and CPU time used. XHProf is a good hierarchical profiler which you can use to generate the callstack and a callgraph of your application (directed acyclic weighted graph) to see where you could start optimizing your application. This talk was presented on the TYPO3 DevDays 2015 in Nuremberg.

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